Imaging System Technology

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Decision Support System (DSS)

Decision Support System (DSS) is a system that combines data, complex analytical models, and user-friendly software in one powerful system. DSS can support semi-structured or unstructured decision-making. DSS is under user control from the start to the implementation into everyday operations. The basic concept of DSS is to give users the tools needed to analyze critical blocks of data using manageable complex models in a flexible way. DSS are designed to provide opportunities not just to respond to the information needs (Khosrow-Pour, 2009).

System of ERP class (Enterprise Resource Planning System) is a corporate information system designed for the automation of planning, accounting, control, and analysis of all the key business aspects. This system processes and solves business issues in the whole enterprise’s (organization) structure. ERP system helps all departments to integrate all functions of the company into a single system where all departments operate and retrieve information using a common database. This makes sharing all sorts of information among them easier.


The application of DSS expands through all the organizational levels. Generally, this system has a positive effect on development. DSS is used in business activities of large-scale trade and e-commerce companies (B2C, B2B), which were the first institutional customers of DSS (Khosrow-Pour, 2009). DSS is also used in banks and financial companies. DSS-systems market in financial institutions is the most capacious now. The scope of DSS-systems in the banks is primarily concerned with retail banking (payment cards and checks), risk analysis, fraud prevention, analysis of consumer behavior, and the design of new financial services. DSS also applies to telecommunications companies, especially mobile communications. In industry, the scope of the DSS-systems includes customer relationship management, statistical inventory management, financial and budgetary planning and management as well as analysis and risk management.

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The use of ERP system includes various functional modules such as accounting and tax accounting, warehouse management, transportation, treasury, personnel records, and customer relationship management (Khosrow-Pour, 2009). Due to the different ERP software modules, a single system is able to replace the outdated disparate information systems for logistics management, finance, inventory, and projects. Therefore, ERP systems are also widely used in various industries and services market.


DSS has a greater analytical power than other systems: it is built with a number of models to analyze the data. DSS are designed to allow users to work with them directly. This system includes a user-friendly software. DSS is an interactive system; the user can change the assumptions and add the new data. An important factor in DSS’s development is the fact that a huge amount of data has accumulated in transactional operational activities of the companies’ management system, the value of which is not accurately used in many ways.

Positive aspects of the ERP implementation in the company are manifested in the reduction of the level of insurance reserves, timely replenishment of material and technical resources, and increasing the turnover of working capital. Also, the benefits of ERP concern illiquid stocks and the number of unplanned purchases, increased production volumes and improved efficiency, effective control of material consumption, better efficiency of pricing and reduction of labor costs on the formation of the financial statements.


DSS may be presented in almost complete transition to a custom configuration of the automotive industry and the ever-increasing range of services in the field of telecommunication services. Information and methods of work will become increasingly important. DSS perfectly suits the continuing trend of transferring direct material production from the developed world to developing countries with low labor costs, energy, and raw materials (Khosrow-Pour, 2009).

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Microsoft Dynamics NAV is an enterprise management system of ERP, which defines its basic functional orientation. This system is designed to control the totality of the company’s resources – money, production facilities, personnel, etc (Khosrow-Pour, 2009). The main purpose of this ERP example is the software of the information space common for all units of the enterprise infrastructure and the provision of comprehensive reliable information for management decisions.

Microsoft BI and OBI

The paper presents (MBI) Microsoft BI and OBI (Oracle Business Intelligence Enterprise Edition). Microsoft BI is a set of products that enable organizations to make decisions based on the reliable information obtained from internal and external data sources. From the point of view of the embodiments of analytical activities, there are three possible scenarios: personal, collective, and corporate analyst (LeBlanc, Moss, Sarka & Ryan, 2015).

OBI is a software platform for solving Business Intelligence problems as interactive and published reports, KPI monitoring, and business processes. It is a descendant of Siebel Analytics (Miller & Hutchinson, 2013).


Microsoft BI solution allows effective managing of any company. Powerful analysis and reporting capabilities in SQL Server Environment provide the infrastructure backbone data management while Microsoft Office applications and Microsoft Office Excel features provide employees, who are engaged in information processing as well as flexible interaction with centralized and secure data sources (LeBlanc, Moss, Sarka & Ryan, 2015). Thus, MBI fits every business.

Like Microsoft BI, OBI suits any type of business where there is a need for business users to receive analytical information on the status of any area of the company, for example, sales volumes in retail stores.


Microsoft BI solution is simple and productive. The affordability of the system software on the market for small and medium businesses (SMB-sector) as well as the prevalence of DBMS Microsoft SQL Server and Microsoft Office use is the key criteria for the choice of this solution.

OBI supports many different data sources including relational databases and OLAP system files (Miller & Hutchinson, 2013). The system allows combining the data from various sources in one report, combining those with each other on specific rules. OBI also has the option of drawing up analysis based on direct queries to the database.


Here is an example of MBI used for the retail trade. The analysis of retail retrieves data using Power View, the tool which as a part of Microsoft BI is ideally suited for interactive data analysis. The MBI can analyze advertising campaigns, sales channels (and the way the sales figures have changed over time), demographic customer data, the location of the outlets on the map (and the level of sales in those outlets), sales by category of goods, etc. The reports, which are to be shown in the demonstration, can be created being based on Excel spreadsheet model (using Power Pivot for Excel) (LeBlanc, Moss, Sarka, & Ryan, 2015). This means that the analyst can prepare data and reports on his own in a matter of days (with the availability of the data produced).

Here is OBI example in retail sale as well. Retail business may already have prepared the running data storage for consistent and consolidated data. Then the problem is simplified because there is the evidence of existing windows and direct access to them from OBI. Typically, these data are arranged in a normalized form being very detailed. OBI windows can be implemented in the form of tables or representations (regular or materialized) (Miller & Hutchinson, 2013). Also, the embodiment is possible when the data is available in the form of OLAP. Then, as a rule, no refinement is required as this means that the multi-dimensional data model has already been built and operated. The existing data are necessary to describe and link to the logical attributes (for example, sales metrics) from the physical attributes on the OLAP server. Multivariate model is constructed based on these data. Model is a description of the data in terms of the facts, measurements, and measuring attributes hierarchies. Then, the developed data model can be transferred to the OBI repository (Miller & Hutchinson, 2013). This is done in the Oracle BI Administration Tool. After the formation of the repository and its uploading to the server, a main phase, which is the development of reports, begins. First, separate tests are developed, and then they are integrated into dashboards. Generally, each developer is working on its own set of analyses and dashboards as there are no options for the joint development (everything happens in the web interface).